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Statistical Techniques for Translating to Morphologically Rich Languages (Dagstuhl Seminar 14061)

Authors Alexander M. Fraser, Kevin Knight, Philipp Koehn, Helmut Schmid, Hans Uszkoreit and all authors of the abstracts in this report



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Alexander M. Fraser
Kevin Knight
Philipp Koehn
Helmut Schmid
Hans Uszkoreit
and all authors of the abstracts in this report

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Alexander M. Fraser, Kevin Knight, Philipp Koehn, Helmut Schmid, and Hans Uszkoreit. Statistical Techniques for Translating to Morphologically Rich Languages (Dagstuhl Seminar 14061). In Dagstuhl Reports, Volume 4, Issue 2, pp. 1-16, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2014)
https://doi.org/10.4230/DagRep.4.2.1

Abstract

This report documents the program and the outcomes of Dagstuhl Seminar 14061 "Statistical Techniques for Translating to Morphologically Rich Languages". The seminar took place in February 2014. The purpose of the seminar was to allow disparate communities working on problems related to morphologically rich languages to meet to discuss an important research problem, translation to morphologically rich languages. While statistical techniques for machine translation have made significant progress in the last 20 years, results for translating to morphologically rich languages are still mixed versus previous generation rule-based systems, so this is a critical and timely topic. Current research in statistical techniques for translating to morphologically rich languages varies greatly in the amount of linguistic knowledge used and the form of this linguistic knowledge. This varies most strongly by target language, for instance the resources currently used for translating to Czech are very different from those used for translating to German. The seminar met a pressing need to discuss the issues involved in these translation tasks in a more broad venue than the ACL Workshops on Machine Translation, which are primarily attended by statistical machine translation researchers. The report describes the introductory material presented to the group, the organization of break-out discussion groups by topic, and the results of the seminar.
Keywords
  • Machine Translation
  • Statistical Machine Translation
  • Syntactic Parsing
  • Morphology
  • Machine Learning
  • Morphologically Rich Languages

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